The present disclosure relates to video coding techniques and, in particular, for developing quantization matrices that perform bandwidth reduction and perceptual/visual quality improvement in video compression operations.
Many modern electronic devices perform video compression. Consumer devices, for example, including laptop computers, notebook computers, tablet computers and smart phones, often capture video information representing local image content and transmit the video information to another device for rendering. Video compression operations exploit temporal and spatial redundancies in the video information to lower its bitrate for transmission over a network.
In one common technique, image data from each input frame is transformed from a pixel-based representation to a frequency-based representation. Thus, the image information is represented as a plurality of transform coefficients, each coefficient representing a frequency component of image information within its domain. Typically, an input frame is partitioned into a plurality of pixel blocks prior to transform and, thus, the transform coefficients provide frequency-domain information regarding the image content within its pixel block.
Further bandwidth compression may be achieved by quantizing the transform coefficients prior to transmission. Quantization involves dividing the transform coefficients by quantization values, which reduces the magnitudes of the transform coefficients. The quantized coefficients typically are transmitted as integer representations, which causes information loss when the quantization does not yield integer values—fractional portions of the quantized coefficients are discarded prior to transmission and cannot be recovered on decode. Thus, quantization poses a tradeoff for designers of video coding systems: Assigning aggressive quantization parameters can lead to good compression of bandwidth but it may induce visual artifacts that impair the perceived quality of the video when it is decoded. On the other hand, assigning low quantization parameters can preserve the perceived quality of the video when it is decoded but contribute little to bandwidth conservation.
The inventors perceive a need for quantization control techniques that adapt flexibly to changing conditions of video capture. Moreover, the inventors perceive a need in the art for quantization control techniques that preserve image information that likely has greatest visual significance.